Modelling Plasmid-Mediated Horizontal Gene Transfer in Biofilms.

In this study, we present a mathematical model for plasmid spread in a growing biofilm, formulated as a nonlocal system of partial differential equations in a 1-D free boundary domain. Plasmids are mobile genetic elements able to transfer to different phylotypes, posing a global health problem when they carry antibiotic resistance factors. We model gene transfer regulation influenced by nearby potential receptors to account for recipient-sensing. We also introduce a promotion function to account for trace metal effects on conjugation, based on literature data. The model qualitatively matches experimental results, showing that contaminants like toxic metals and antibiotics promote plasmid persistence by favoring plasmid carriers and stimulating conjugation. Even at higher contaminant concentrations inhibiting conjugation, plasmid spread persists by strongly inhibiting plasmid-free cells. The model also replicates higher plasmid density in biofilm's most active regions.

A Mathematical Study of Metal Biosorption on Algal-Bacterial Granular Biofilms.

A multiscale mathematical model describing the metals biosorption on algal-bacterial photogranules within a sequencing batch reactor (SBR) is presented. The model is based on systems of partial differential equations (PDEs) derived from mass conservation principles on a spherical free boundary domain with radial symmetry. Hyperbolic PDEs account for the dynamics of sessile species and their free sorption sites, where metals are adsorbed. Parabolic PDEs govern the diffusion, conversion and adsorption of nutrients and metals. The dual effect of metals on photogranule ecology is also modelled: metal stimulates the production of EPS by sessile species and negatively affects the metabolic activities of microbial species. Accordingly, a stimulation term for EPS production and an inhibition term for metal are included in all microbial kinetics. The formation and evolution of the granule domain are governed by an ordinary differential equation with a vanishing initial value, accounting for microbial growth, attachment and detachment phenomena. The model is completed with systems of impulsive differential equations describing the evolution of dissolved substrates, metals, and planktonic and detached biomasses within the granular-based SBR. The model is integrated numerically to examine the role of the microbial species and EPS in the adsorption process, and the effect of metal concentration and adsorption properties of biofilm components on the metal removal. Numerical results show an accurate description of the photogranules evolution and ecology and confirm the applicability of algal-bacterial photogranule technology for metal-rich wastewater treatment.

Dynamic modelling the effects of ionic strength and ion complexation on trace metal speciation during anaerobic digestion.

Dosing trace metals into anaerobic digestors is proven to improve biogas production rate and yield by stimulating microorganisms involved in the metabolic pathways. Trace metal effects are governed by metal speciation and bioavailability. Though chemical equilibrium speciation models are well-established and widely used to understand metal speciation, the development of kinetic models considering biological and physicochemical processes has recently gained attention. This work proposes a dynamic model for metal speciation during anaerobic digestion which is based on a system of ordinary differential equations aimed to describe the kinetics of biological, precipitation/dissolution, gas transfer processes and, a system of algebraic equations to define fast ion complexation processes. The model also considers ion activity corrections to define effects of ionic strength. Results from this study shows the inaccuracy in predicting trace metal effects on anaerobic digestion by typical metal speciation models and the significance of considering non-ideal aqueous phase chemistry (ionic strength and ion pairing/complexation) to define speciation and metal labile fractions. Model results show a decrease in metal precipitation and increase in metal dissolved fraction and methane production yield with increase in ionic strength. Capability of the model to dynamically predict trace metal effects on anaerobic digestion under different conditions, like changing dosing conditions and initial iron to sulphide ratio, was also tested and verified. Dosing iron increases methane production and decreases hydrogen sulphide production. However, when iron to sulphide ratio is greater than 1, methane production decreases due to increase in dissolved iron which reaches inhibitory concentration levels.

A comprehensive review of mathematical models of photo fermentation.

This work aims at analyzing and comparing the different modeling approaches used to date to simulate, design and control photo fermentation processes for hydrogen production and/or wastewater treatment. The study is directed to researchers who approach the problem of photo fermentation mathematical modeling. It is a useful tool to address future research in this specific field in order to overcome the difficulty of modeling a complex, not totally elucidate process. We report a preliminary identification of the environmental and biological parameters, included in the models, which affect photo fermentation. Based on model features, we distinguish three different approaches, i.e. kinetic, parametric and non-ideal reactors. We explore the characteristics of each approach, reporting and comparing the obtained results and underlining the differences between models, together with the advantages and the limitations of each of them. The analysis of the approaches indicates that Kinetic models are useful to describe the process from a biochemical point of view, without considering bio-reactor hydrodynamics and the spatial variations that Parametric Models can be utilized to study the influence and the interactions between the operational conditions. They do not take into account the biochemical process mechanism and the influence of reactor hydrodynamics. Quite the opposite, non-ideal reactors models focus on the reactor configuration. Otherwise, the biochemical description of purple non-sulfur bacteria activities is usually simplified. This review indicates that there still is a lack of models that fully describe photo fermentation processes.

Nutrient removal efficiency of green algal strains at high phosphate concentrations.

The effects of autotrophic and mixotrophic conditions on microalgae growth and nutrient removal efficiency from synthetic wastewater by different microalgae were investigated. Although several studies have demonstrated the suitability of microalgae technologies for ammonia-rich wastewater treatment, only a few have been used for treatment of phosphate-rich industrial wastewaters. In this work, six microalgae were cultivated in batch mode in a growth medium with a high phosphate concentration (0.74 Mm PO4 3--P) and different carbon sources (ammonium acetate and sodium bicarbonate) without CO2 supplementation or pH adjustment. Their potential for nutrient removal and biomass generation was estimated. The biomass growth in the reactors was modeled and the data aligned to the Verhulst model with R2 > 0.93 in all cases. Chlorella pyrenoidosa ACUF_808 showed the highest final biomass productivity of 106.21 and 75.71 mg·L-1·d-1 in media with inorganic and organic carbon sources, respectively. The highest phosphorus removal efficiency was 32% with Chlorella vulgaris ACUF_809, while the nitrate removal efficiency in all reactors exceeded 93%. The coupled cultivation of the novel isolated strains of C. pyrenoidosa and C. vulgaris under mixotrophic conditions supplemented with ammonium acetate might be a promising solution for simultaneous nitrate and phosphate removal from phosphorus-rich wastewaters.

Elemental sulfur-based autotrophic denitrification and denitritation: microbially catalyzed sulfur hydrolysis and nitrogen conversions.

The hydrolysis of elemental sulfur (S0) coupled to S0-based denitrification and denitritation was investigated in batch bioassays by microbiological and modeling approaches. In the denitrification experiments, the highest obtained NO3--N removal rate was 20.9 mg/l·d. In the experiments with the biomass enriched on NO2-, a NO2--N removal rate of 10.7 mg/l·d was achieved even at a NO2--N concentration as high as 240 mg/l. The Helicobacteraceae family was only observed in the biofilm attached onto the chemically-synthesized S0 particles with a relative abundance up to 37.1%, suggesting it was the hydrolytic biomass capable of S0 solubilization in the novel surface-based model. S0-driven denitrification was modeled as a two-step process in order to explicitly account for the sequential reduction of NO3- to NO2- and then to N2 by denitrifying bacteria.

Start-up of an anaerobic fluidized bed reactor treating synthetic carbohydrate rich wastewater.

The present work studied the start-up process of a mesophilic (37 ± 2 °C) anaerobic fluidized bed reactor (AFBR) operated at a hydraulic retention time (HRT) of 20 days using synthetic carbohydrate rich wastewater. Anox Kaldness-K1 carriers were used as biofilm carrier material. The reactor performance and biofilm formation were evaluated during the process. The start-up process at lower liquid recirculation flow rate enhanced the biofilm formation and reactor performance. The organic substrate composition had a major impact on early colonization of methanogenic archaea onto the surface of the Kaldness carriers during the start-up process. Specific organic substrates favouring the growth of methanogenic archaea, such as acetate, are preferred in order to facilitate the subsequent biofilm formation and AFBR start-up. The supply of 'bio-available' nutrients and trace elements, in particular iron, had an important role on optimal methanogenic activity and speeding-up of the biofilm development on the Kaldness carriers. This paper provides possible strategies to optimize the various operational parameters that influence the initial biofilm formation and development in an AFBR and similar high rate anaerobic reactors, hence can be used to reduce the long time required for process start-up.

Dark fermentation of complex waste biomass for biohydrogen production by pretreated thermophilic anaerobic digestate.

The Biohydrogen Potential (BHP) of six different types of waste biomass typical for the Campania Region (Italy) was investigated. Anaerobic sludge pre-treated with the specific methanogenic inhibitor sodium 2-bromoethanesulfonic acid (BESA) was used as seed inoculum. The BESA pre-treatment yielded the highest BHP in BHP tests carried out with pre-treated anaerobic sludge using potato and pumpkin waste as the substrates, in comparison with aeration or heat shock pre-treatment. The BHP tests carried out with different complex waste biomass showed average BHP values in a decreasing order from potato and pumpkin wastes (171.1 ± 7.3 ml H2/g VS) to buffalo manure (135.6 ± 4.1 ml H2/g VS), dried blood (slaughter house waste, 87.6 ± 4.1 ml H2/g VS), fennel waste (58.1 ± 29.8 ml H2/g VS), olive pomace (54.9 ± 5.4 ml H2/g VS) and olive mill wastewater (46.0 ± 15.6 ml H2/g VS). The digestate was analyzed for major soluble metabolites to elucidate the different biochemical pathways in the BHP tests. These showed the H2 was produced via mixed type fermentation pathways.

Thermal pretreatment of olive mill wastewater for efficient methane production: control of aromatic substances degradation by monitoring cyclohexane carboxylic acid.

Anaerobic digestion is investigated as a sustainable depurative strategy of olive oil mill wastewater (OOMW). The effect of thermal pretreatment on the anaerobic biodegradation of aromatic compounds present in (OMWW) was investigated. The anaerobic degradation of phenolic compounds, well known to be the main concern related to this kind of effluents, was monitored in batch anaerobic tests at a laboratory scale on samples pretreated at mild (80±1 °C), intermediate (90±1 °C) and high temperature (120±1 °C). The obtained results showed an increase of 34% in specific methane production (SMP) for OMWW treated at the lowest temperature and a decrease of 18% for treatment at the highest temperature. These results were related to the different decomposition pathways of the lignocellulosic compounds obtained in the tested conditions. The decomposition pathway was determined by measuring the concentrations of volatile organic acids, phenols, and chemical oxygen demand (COD) versus time. Cyclohexane carboxylic acid (CHCA) production was identified in all the tests with a maximum concentration of around 200 µmol L(-1) in accordance with the phenols degradation, suggesting that anaerobic digestion of aromatic compounds follows the benzoyl-CoA pathway. Accurate monitoring of this compound was proposed as the key element to control the process evolution. The total phenols (TP) and total COD removals were, with SMP, the highest (TP 62.7%-COD 63.2%) at 80 °C and lowest (TP 44.9%-COD 32.2%) at 120 °C. In all cases, thermal pretreatment was able to enhance the TP removal ability (up to 42% increase).

Modified Anaerobic Digestion Model No.1 for dry and semi-dry anaerobic digestion of solid organic waste.

The role of total solids (TS) content in anaerobic digestion of selected complex organic matter, e.g. rice straw and food waste, was investigated. A range of TS from wet (4.5%) to dry (23%) was evaluated. A modified version of the Anaerobic Digestion Model No.1 for a complex organic substrate is proposed to take into account the effect of the TS content on anaerobic digestion. A linear function that correlates the kinetic constants of three specific processes (i.e. disintegration, acetate and propionate up-take) was included in the model. Results of biomethanation and volatile fatty acids production tests were used to calibrate the proposed model. Model simulations showed a good agreement between numerical and observed data.

Enhanced anaerobic digestion of food waste by thermal and ozonation pretreatment methods.

Treatment of food waste by anaerobic digestion can lead to an energy production coupled to a reduction of the volume and greenhouse gas emissions from this waste type. According to EU Regulation EC1774/2002, food waste should be pasteurized/sterilized before or after anaerobic digestion. With respect to this regulation and also considering the slow kinetics of the anaerobic digestion process, thermal and chemical pretreatments of food waste prior to mesophilic anaerobic digestion were studied. A series of batch experiments to determine the biomethane potential of untreated as well as pretreated food waste was carried out. All tested conditions of both thermal and ozonation pretreatments resulted in an enhanced biomethane production. The kinetics of the anaerobic digestion process were, however, accelerated by thermal pretreatment at lower temperatures (<120 °C) only. The best result of 647.5 ± 10.6 mlCH4/gVS, which is approximately 52% higher as compared to the specific biomethane production of untreated food waste, was obtained with thermal pretreatment at 80 °C for 1.5 h. On the basis of net energy calculations, the enhanced biomethane production could cover the energy requirement of the thermal pretreatment. In contrast, the enhanced biomethane production with ozonation pretreatment is insufficient to supply the required energy for the ozonator.

Effect of moisture on disintegration kinetics during anaerobic digestion of complex organic substrates.

The role of the moisture content and particle size (PS) on the disintegration of complex organic matter during the wet anaerobic digestion (AD) process was investigated. A range of total solids (TS) from 5% to 11.3% and PS from 0.25 to 15 mm was evaluated using carrot waste as model complex organic matter. The experimental results showed that the methane production rate decreased with higher TS and PS. A modified version of the AD model no.1 for complex organic substrates was used to model the experimental data. The simulations showed a decrease of the disintegration rate constants with increasing TS and PS. The results of the biomethanation tests were used to calibrate and validate the applied model. In particular, the values of the disintegration constant for various TS and PS were determined. The simulations showed good agreement between the numerical and observed data.

Metformin and lamotrigine sorption on a digestate amended soil in presence of trace metal contamination.

The antidiabetic drug metformin and antiepileptic drug lamotrigine are contaminants of emerging concern that have been detected in biowaste-derived amendments and in the environment, and their fate must be carefully studied. This work aimed to evaluate their sorption behaviour on soil upon digestate application. Experiments were conducted on soil and digestate-amended soil as a function of time to study kinetic processes, and at equilibrium also regarding the influence of trace metals (Pb, Ni, Cr, Co, Cu, Zn) at ratio pharmaceutical/metal 1/1, 1/10, and 1/100. Pharmaceutical desorption experiments were also conducted to assess their potential mobility to groundwater. Results revealed that digestate amendment increased metformin and lamotrigine adsorbed amounts by 210% and 240%, respectively, increasing organic matter content. Metformin adsorption kinetics were best described by Langmuir model and those of lamotrigine by Elovich and intraparticle diffusion models. Trace metals did not significantly affect the adsorption of metformin in amended soil while significantly decreased that of lamotrigine by 12-39%, with exception for Cu2+ that increased both pharmaceuticals adsorbed amounts by 5 - 8%. This study highlighted the influence of digestate amendment on pharmaceutical adsorption and fate in soil, which must be considered in the circular economy scenario of waste-to-resource.

A mechanistic mathematical model for photo fermentative hydrogen and polyhydroxybutyrate production.

An original mathematical model describing the photo fermentation process is proposed. The model represents the first attempt to describe the photo fermentative hydrogen production and polyhydroxybutyrate accumulation, simultaneously. The mathematical model is derived from mass balance principles and consists of a system of ordinary differential equations describing the biomass growth, the nitrogen and the substrate degradation, the hydrogen and other catabolites production, and the polyhydroxybutyrate accumulation in photo fermentation systems. Moreover, the model takes into account important inhibiting phenomena, such as the self-shading and the substrate inhibition, which can occur during the evolution of the process. The calibration was performed using a real experimental data set and it was supported by the results of a sensitivity analysis study. The results showed that the most sensitive parameters for both hydrogen and PHB production were the hydrogen yield on substrate, the catabolites yield on substrate, and the biomass yield. Successively, a different experimental data set was used to validate the model. Performance indicators showed that the model could efficiently be used to simulate the photo fermentative hydrogen and polyhydroxybutyrate production by Rhodopseudomonas palustris. For instance, the index of agreement of 0.95 was observed for the validated hydrogen production trend. Moreover, the model well predicted the maximum PHB accumulation in bacterial cells. Indeed, the predicted and observed accumulated PHB were 4.5 and 4.8%, respectively. Further numerical simulations demonstrated the model consistency in describing process inhibiting phenomena. Numerical simulations showed that the acetate and nitrogen inhibition phenomena take place when concentrations are higher than 12.44 g L-1 and lower than 4.76 mg L-1, respectively. Finally, the potential long term hydrogen production from accumulated polyhydroxybutyrate in bacterial cells was studied via a fast-slow analysis technique.

A transient biological fouling model for constant flux microfiltration.

Microfiltration is a widely used engineering technology for fresh water production and water treatment. The major concern in many applications is the formation of a biological fouling layer leading to increased hydraulic resistance and flux decline during membrane operations. The growth of bacteria constituting such a biological layer implicates the formation of a multispecies biofilm and the consequent increase of operational costs for reactor management and cleaning procedures. To predict the biofouling evolution, a mono-dimensional continuous free boundary model describing biofilm dynamics and EPS production in different operational phases of microfiltration systems has been well studied. The biofouling growth is governed by a system of hyperbolic PDEs. Substrate dynamics are modeled through parabolic equations accounting for diffusive and advective fluxes generated during the filtration process. The free boundary evolution depends on both microbial growth and detachment processes. What is not addressed is the interplay between biofilm dynamics, filtration, and water recovery. In this study, filtration and biofilm growth modeling principles have been coupled for the definition of an original mathematical model able to reproduce biofouling evolution in membrane systems. The model has been solved numerically to simulate biologically relevant conditions, and to investigate the hydraulic behavior of the membrane. It has been calibrated and validated using lab-scale data. Numerical results accurately predicted the pressure drop occurring in the microfiltration system. A calibrated model can give information for optimization protocols as well as fouling prevention strategies.

Enhanced bio-methane production from co-digestion of different organic wastes.

This paper deals with an experimental study aimed at assessing the effect of mixing different organic wastes on the anaerobic digestion process. Livestock manure and organic solid wastes have been taken into account as substrates to verify if their mixing gives rise to higher methane production rates and lower risk of process failure. Bio-methane potential (BMP) tests have been conducted using the following substrates: buffalo manure (BM), poultry manure (PM), organic fraction of the municipal solid waste (OFMSW), greengrocery waste (GW) and two different mixtures composed of BM and OFMSW. Mixing BM with OFMSW resulted in 12% and 30% higher methane volumes after 30 and 15 days from the test start, respectively. Experimental data have been also used to calibrate and validate a mathematical model previously proposed by the authors, showing its capability to reproduce the synergistic effect on methane production promoted by co-digesting BM and OFSMW.

Mathematical modeling of metal recovery from E-waste using a dark-fermentation-leaching process.

In this work, an original mathematical model for metals leaching from electronic waste in a dark fermentation process is proposed. The kinetic model consists of a system of non-linear ordinary differential equations, accounting for the main biological, chemical, and physical processes occurring in the fermentation of soluble biodegradable substrates and in the dissolution process of metals. Ad-hoc experimental activities were carried out for model calibration purposes, and all experimental data were derived from specific lab-scale tests. The calibration was achieved by varying kinetic and stoichiometric parameters to match the simulation results to experimental data. Cumulative hydrogen production, glucose, organic acids, and leached metal concentrations were obtained from analytical procedures and used for the calibration. The results confirmed the high accuracy of the model in describing biohydrogen production, organic acids accumulation, and metals leaching during the biological degradation process. Thus, the mathematical model represents a useful and reliable tool for the design of strategies for valuable metals recovery from waste or mineral materials. Moreover, further numerical simulations were carried out to analyze the interactions between the fermentation and the leaching processes and to maximize the efficiency of metals recovery due to the fermentation by-products.

Multiscale modelling of the start-up process of anammox-based granular reactors.

This work proposes a mathematical model on partial nitritation/anammox (PN/A) granular bioreactors, with a particular interest in the start-up phase. The formation and growth of granular biofilms is modelled by a spherical free boundary problem with radial symmetry and vanishing initial value. Hyperbolic PDEs describe the advective transport and growth of sessile species inhabiting the granules. Parabolic PDEs describe the diffusive transport and conversion of soluble substrates, and the invasion process mediated by planktonic species. Attachment and detachment phenomena are modelled as continuous and deterministic fluxes at the biofilm-bulk liquid interface. The dynamics of planktonic species and substrates within the bulk liquid are modelled through ODEs. A simulation study is performed to describe the start-up process of PN/A granular systems and the development of anammox granules. The aim is to investigate the role that the invasion process of anaerobic ammonia-oxidizing (anammox) bacteria plays in the formation of anammox granules and explore how it affects the microbial species distribution of anaerobic ammonia-oxidizing, aerobic ammonia-oxidizing, nitrite-oxidizing and heterotrophic bacteria. Moreover, the model is used to study the role of two key parameters in the start-up process: the anammox inoculum size and the inoculum addition time. Numerical results confirm that the model can be used to simulate the start-up process of PN/A granular systems and to predict the evolution of anammox granular biofilms, including the ecology and the microbial composition. In conclusion, after being calibrated, the proposed model could provide quantitatively reliable results and support the start-up procedures of full-scale PN/A granular reactors.

Modelling the effect of SMP production and external carbon addition on S-driven autotrophic denitrification.

The aim of this study was to develop a mathematical model to assess the effect of soluble microbial products production and external carbon source addition on the performance of a sulfur-driven autotrophic denitrification (SdAD) process. During SdAD, the growth of autotrophic biomass (AUT) was accompanied by the proliferation of heterotrophic biomass mainly consisting of heterotrophic denitrifiers (HD) and sulfate-reducing bacteria (SRB), which are able to grow on both the SMP derived from the microbial activities and on an external carbon source. The process was supposed to occur in a sequencing batch reactor to investigate the effects of the COD injection on both heterotrophic species and to enhance the production and consumption of SMP. The mathematical model was built on mass balance considerations and consists of a system of nonlinear impulsive differential equations, which have been solved numerically. Different simulation scenarios have been investigated by varying the main operational parameters: cycle duration, day of COD injection and quantity of COD injected. For cycle durations of more than 15 days and a COD injection after the half-cycle duration, SdAD represents the prevailing process and the SRB represent the main heterotrophic family. For shorter cycle duration and COD injections earlier than the middle of the cycle, the same performance can be achieved increasing the quantity of COD added, which results in an increased activity of HD. In all the performed simulation even in the case of COD addition, AUT remain the prevailing microbial family in the reactor.